METHODS AND SYSTEMS FOR PREDICTIVE ENGINE EVALUATION AND REPLAY OF ENGINE PERFORMANCE

Disclosed are methods and systems of tracking the deployment of a predictive engine for machine learning, including steps to deploy an engine variant of the predictive engine based on an engine parameter set, wherein the engine parameter set identifies at least one data source and at least one algorithm; receive one or more queries to the deployed engine variant from one or more end-user devices, and in response, generate predicted results; receive one or more actual results corresponding to the predicted results; associate the queries, the predicted results, and the actual results with a replay tag, and record them with the corresponding deployed engine variant.